- Email: [email protected]
The impact of the ivory trade on the African elephant Loxodonta africana population as assessed by data from the trade
Biological Conservation 55 (1991) 215-229
The Impact of the Ivory Trade on the African Elephant Loxodonta africana Population as Assessed by Data from the Trade
E. J. Milner-Gulland & Ruth Mace* Renewable Resources Assessment Group, Imperial College Centre for Environmental Technology, 8 Princes Gardens, London SW7 1NA, UK (Received 25 April 1990; accepted 30 June 1990)
A BSTRA CT Data on the total quantity and tusk sizes of African elephant Loxodonta africana ivory entering the international trade over the last decade are reviewed. This work investigated how different levels of hunting and different strengths of selectivity by hunters in favour of larger tusks would produce different ivory tonnages and tusk size distributions in the trade. It shows that the removal of about 12-13% of elephants with tusks each year, combined with hunters showing a preference for elephants with larger tusks, would be expected to produce quantities of ivory and tusk size distributions compatible with those reported in international trade.
INTRODUCTION The ivory trade in Africa has a long history, recounted in detail by Parker (1979). At the turn of the century, volumes of trade were high. With the collapse of the slave trade (with which the ivory trade was intimately associated) and the coming of the two world wars, hunting was much reduced. Volumes of trade grew slowly through the 1950s and 1960s but it was only in the 1970s, as Asian and Far Eastern countries--especially Japan--became wealthy, that a massive increase in elephant (Loxodonta * Present address: School of Development Studies, University of East Anglia, Norwich NR4 7JT, UK. 215 Biol. Conserv. 0006-3207/90/$03'50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Great Britain
216
E. J. Milner-Gulland, Ruth Mace
africana) hunting occurred. The elephant population had to supply a new demand as large as, or larger than, that of the colonial period. In order to explore the way in which harvesting could affect elephant populations, we constructed a Leslie matrix model (Leslie, 1945), which tracks the population through time, by age-class and sex. This approach is particularly appropriate for the exploration of the effects of trade on elephant populations since the relationship between tusk size and age is described by a power law for both sexes, but male tusks grow at a much faster rate than female tusks (Pilgram & Western, 1986a). Since male tusks are visible at a younger age they also start to be hunted at a younger age than females. If any form of selectivity in favour of larger tusks occurs, then males and older animals will suffer more hunting than females and immatures. It is therefore important that the age and sex structure of the population be taken into account. There have been several models of elephant population biology that use the Leslie matrix, for example to model the relationship between elephant populations and their habitats (Fowler & Smith, 1973; Wu & Botkin, 1980) and to model elephant harvesting strategies (Pilgram & Western, 1986b; Getz & Haight, 1989). In this study we used a Leslie matrix model to help interpret actual data from the international ivory trade.
D A T A SOURCES Two complementary types of trade data were used to assess the impact of trade on the African elephant population: the total biomass in international trade and the size distribution of tusks in the trade. Estimates of the total biomass of ivory in international trade give only a limited idea of the number of elephants killed to supply the trade without data on the mean tusk weight in the trade. Tusk weight distributions provide mean tusk weights, together with some information on the age and sex composition of the offtake and thus, the population. Each source of data has the potential for considerable inaccuracy, but by using both we can see to what extent a consistent story emerges about the nature and consequences of the hunting that has occurred to supply the international ivory trade. Estimates of elephant population size give some indication of population change over the decade, which can be compared to that given by the trade data.
Population surveys Data on population size are available from various sources for the period 1979-89, but they are subject to large margins of error due to changes in
Ivory trade and the African elephant
217
sampling methods and estimation techniques and to a large component of extrapolation (Burrill & Douglas-Hamilton, 1987). There is particular uncertainty as to the number of elephants in the central African forests. Estimates for 1987 and 1989 have been revised on the basis of recent survey work in these forests (Barnes, 1989), and are thought to be much more accurate than previous estimates, partly due to the use of the UNEP G R I D system to extrapolate from the best available data for each region of Africa.
Exports of ivory from Africa Data on the volume of trade in ivory over the period 1979-87 are available for each ivory exporting country in Africa (Luxmoore et al., 1989). These are predominately customs records from importing countries, indicating from which country the ivory came, which tend to be more reliable than records from exporting countries. The mean annual export of raw ivory from Africa has been over 700 tonnes for the last decade. The figure was somewhat higher than this in the early 1980s and has been declining gradually throughout the decade. It dropped particularly steeply in 1987, although Luxmoore et al. (1989) advise treating this last figure with caution. All estimates of the volume of the ivory trade must be treated as minima since not only do they exclude ivory carved within the country of origin, but also an unknown proportion of illicit trade. Although it is clear that the hunting pressure on the African elephant is heterogeneous, the characteristics of the ivory trade are such that it would be unwise to attempt to relate a country's exports directly to changes in that country's elephant population, and so to build up a less superficial view of the effects of the trade on elephant populations. The illicit nature of much of the ivory trade means that the exports of a particular country may have more to do with the efficiency of its Customs and border patrols, and the strength of its currency, than the status of its elephant population. Africa-wide exports at least tell us the total volume of ivory removed from the total population.
The size of tusks in the trade The weights of individual tusks legally exported from various countries in Africa between 1986 and 1988 are available from an analysis of CITES export permits in those years by the Wildlife Trade Monitoring Unit of the International Union for the Conservation of Nature. For the majority of countries the median tusk weight is below 5 kg, but the exports of three countries (Congo, Gabon, Zimbabwe) have median tusk weights around 10kg, indicating that these countries were exporting only a selection of larger tusks. A smaller sample of tusks from the government ivory stores of
218
E. J. Milner-Gulland, Ruth Mace
various African countries in the period 1979-1981 was also analysed. The mean tusk weight for the 1979-81 sample, with the mean tusk weight from each country weighted according to its total exports, is 4-97 kg, and for the 1986-88 sample 4.52 kg (excluding the above-named selective exporters). Tusk weight distributions are also available for the Singapore stockpile registered by CITES in 1986, and for ivory confiscated in Tanzania over the period 1971-77 and in Kenya in 1986-88 (I. Douglas-Hamilton, pers. comm.). The sample sizes and mean and median tusk weights for the samples are shown in Table 1. Tusk weight distributions tend to be very skewed towards smaller tusks, as is shown by the difference between the mean and median. There is no evidence from the above tusk weight distributions that the mean tusk weight o f ivory entering the trade has declined greatly since 1979. For the three countries where there are data in more than one time period, one country showed a small increase in mean tusk weight, one a small decrease and one an increase followed by a decrease. Data collected from major importing countries do seem to show a decline in mean tusk weight over this period, this being rather sharp in some cases (Milliken, 1989; Milliken & Melville, 1989). These data must be interpreted with great care, since importing countries are selective in their buying, and this is reflected
TABLE 1
Total Numbers of Tusks for which Mean and Median Tusk Weights were Available, including only those Countries with a Total Sample Size of at least 1000 Tusks Country
1979-81 Sample size
Burundi Congo Djibouti Gabon Kenya Mozambique Sudan Tanzania (1971-77) Singapore South Africa Zambia Zaire Zimbabwe
Mean
1986-88 Median
835
4.20
2-61
2 639 44 055
5-09 4.98
3'60 3.41
1 302
4.85
3.61
Sample size
Mean
Median
17841 5 392 1981 1 532 1957 3 049 33 580 8 488
4.95 12.43 5"49 11.74 5'60 5.71 3.54 4"57
3.32 11.32 3.39 10'53 4.27 3.62 2.11 2'86
52 823 10 640 2 723 4 283 1481
4-87 7"11 4"37 4,39 11,37
3"33 4.48 2.87 2.57 9-11
All data supplied by WTMU except the confiscated tusks from Kenya and Tanzania, supplied by I. Douglas-Hamilton (pers. comm.).
Ivory trade and the African elephant
219
in the large difference in mean tusk weights imported by different countries. The mean weight of all tusks circulating in world trade (Milliken, 1989), was much lower in 1986-87 than in the previous few years.
A S I M U L A T I O N M O D E L OF E L E P H A N T P O P U L A T I O N DYNAMICS: A S S U M P T I O N S A N D P A R A M E T E R VALUES In a Leslie matrix model, the number of animals in each age-class in a year is calculated as the number of animals in the previous age class in the previous year, minus those that died as a result of natural mortality or hunting. The number of animals in the first age-class is calculated from the number of calves that the female population would have given birth to in the previous year. We assume that animals with tusks of less than 1 kg (i.e. females less than nine years old and males younger than six) are not hunted, as tusks smaller than this are rare in the trade. But although calves are not killed directly many die when their mothers are killed. Poole (1989) gives data on the mortality rates of orphaned calves, which are incorporated in the model. Mortality is taken to occur sequentially, with half the natural mortality occurring first, followed by hunting mortality and incidental calf mortality caused by orphaning, then the other half of the natural mortality. Finally, recruitment occurs. The tusk weight distributions of offtake produced by the model includes only hunted elephants. Natural mortality tusks (including those from orphaned calves) are assumed not to be found. Studies have shown that even in the best-patrolled national parks, the finding rate for natural mortality tusks is less than 6% of those available (Douglas-Hamilton, 1979), and so it is unlikely that natural mortality makes up a large proportion of trade. This is particularly so at high levels of hunting mortality, when few adult animals will survive long enough to die a 'natural death', and the smaller tusks resulting from the deaths of immatures are much more likely to disintegrate or be eaten by hyaenas, as well as being harder to locate. The parameter values used in the model are shown in Table 2. In reality there will be considerable variation between populations due to a variety of factors such as rainfall, which will vary locally and from year to year; the values given are therefore averages. Density-dependent effects on reproduction are not included in the model, unlike in other models of the effects of harvesting on elephant populations (Pilgram & Western, 1986a). This is because of the fact that, as a large mammal with a low intrinsic rate of reproduction, the elephant is only likely to show significantly reduced reproduction due to high population density when at over 75-80% of carrying capacity (Fowler, 1981, 1984). Studies of
E.J. Milner-Gulland, Ruth Mace
220
t~
~=~
"8 o
~o
.~
.~ 0 e~
o
"~
0
0 .0
0
.,-
<.=. 0 .~,
.=
0
r~
0
I
O
e-,
u~ ell
_= > r~
E
2 .~
E
.m
~ ~ ~ ~ -~ ~ - ~ ~
~ ~ ~
.~ ~
._="
E
~
.o ~ ~
~
~
'~.~
~ ~
e-,
o
r.~
z
Ivory trade and the African elephant
221
the density of elephant populations (Douglas-Hamilton, 1988) suggest that it is only in a very few parks that densities may approach these high levels and we assume that this was already the case by 1979. More worrying is the suggestion by Poole (1989) that reproductive rates drop at high hunting levels due to a shortage of males and/or social disruption, in some cases dramatically. We assume an interbirth interval of five years. Whereas populations that are at low densities but are freed from hunting may be breeding faster than we have estimated, populations that are being lowered by continuous poaching may be breeding very much more slowly. Decreasing the assumed interbirth interval reduced the goodness of fit in the analyses presented in our results, while increasing it made little difference. Thus, a five-year interbirth interval seems a realistic assumption. Selectivity was modelled assuming that hunter preference was related to the weight of the tusk (see Table 2). A selectivity of 0 means that each age class is hunted in proportion to the frequency with which it appears in the population. Thus, at a 12% hunting mortality, 12% of each age class is taken per year. A selectivity of 1 means that tusks are preferred directly in proportion to their weight, for example an elephant with 6 kg tusks is twice as likely to be hunted as one with 3 kg tusks. A selectivity of 2 means that the 6 kg tusker is four times as likely to be hunted as the 3 kg tusker. The hunting mortalities in this paper are expressed as the proportion of the total number of animals available for hunting that is killed each year. This proportion is divided among the age-classes according to the strength of the selectivity. If the hunting mortality were taken as a proportion of the whole population, it would be lower. However, the deaths of orphaned calves as an indirect result of hunting mean that the hunting-induced mortality in these age-classes is approximately the same as that for adult females. Exact figures depend on the age and sex structure of the population. The model shows that a population with these dynamics would remain stable and stationary if no more than 3.5 % of the available age-classes were hunted per year (note that this is higher than the hunting rate that would yield the maximum sustainable yield in terms of ivory biomass (M. Basson, pers. comm.). This figure is similar to that estimated, by a different method, to be an appropriate culling rate to keep elephant populations in Zimbabwe at a stable size (Craig, 1989). RESULTS
The effect of hunting patterns on the size of tusks entering the trade The strategy used to hunt elephants will have a direct effect on the weight distribution of tusks in the trade, and thus on the biomass produced when a
222
E. J. Milner-Gulland, Ruth Mace
particular number of animals is killed. This study explored the effects on population size and ivory supply of varying both the proportion of the population taken each year and the strength of the selectivity shown by hunters for larger tusks. When a pristine population is first subjected to hunting the size of tusks harvested will decline. If the hunters are not selective, then tusks in the trade will reflect those in the population (except calves with tusks of less than 1 kg). Mean tusk size harvested will decline as the mean age of the population declines. The greater the selectivity for larger tusks, the faster the rate of initial decline in mean tusk weight as adult males, and then younger males and adult females are removed from the population at a disproportionate rate. Whilst this decline is initially rapid, the tusk size distribution produced soon reaches a state of relative stability or negligible decline, where it remains until extinction occurs. For any given hunting mortality, the higher the selectivity, the lower the mean tusk weight at which the population (and offtake) stabilises. The weight distribution of tusks in the trade stabilises even while the population size is declining rapidly. If hunting were at 12% per year with selectivity 1, then the mean tusk weight would fall by 10kg in the first 10 years, then by less than 1 kg in the next 40 years, while the population halved every 10 years. When fitting total ivory tonnages we assume that populations are no longer in the phase of rapid decline but in the relatively stable phase, given the tusk weight data shown above. Although it is unlikely that most populations are stable, the data suggest that most are not in the phase of rapid decline. Thus, for a given set of life history parameters, the combination of the hunting mortality and selectivity applied to a population will determine the rate of decline of that population, the tonnes of ivory produced and the size distribution of the tusks. Finding the best fit to available data
The combination of hunting mortality and selectivity that minimises the sum of squares of the residuals between the result predicted by the model and observed data (i.e. the least squares fit) is calculated for (i) biomass in the trade since 1979; (ii) biomass in the trade since 1979 and the 1979 population estimate; (iii) the tusk weight distribution of the Singapore stockpile. The population size in 1987 is fixed at 720 000 animals (Douglas-Hamilton, 1988) because the 1987 population estimate is considered to be the most accurate datapoint available. The biomass reported in international trade since 1979 best fits an annual
Ivory trade and the African elephant
223
1100 -I
900 Z Z
800
O [..
es~
700
.< (D
-1,-__
600 50O 400 300 1979
1 80
' 1981
19~82
' 1983 YEAR
' 1984
~ 1985
' 1986
1987
Fig. I. T o t a l b i o m a s s in t o n n e s o f ivory e x p o r t e d f r o m Africa in the years 1979-87, with e x p e c t e d b i o m a s s u n d e r the h u n t i n g p a t t e r n that m i n i m i s e s the least s q u a r e s fit b e t w e e n m o d e l o u t p u t a n d b i o m a s s data. D a t a f r o m L u x m o o r e et al. (1989). P o p u l a t i o n size for 1987 is fixed at 720000.
hunting mortality of 12"6% at a selectivity of 0.1 (Fig. 1). Figure 2(a) shows how sensitive this fit is to variation in hunting mortality and selectivity. Hunting mortalities of less than 12% do not produce a good fit at any level of selectivity. Hunting mortalities as high as 17% do give a reasonable fit as long as the selectivity is high. If such high levels of hunting mortality have occurred, then the 1979 population estimate of 1 340000 elephants (Burrill & Douglas-Hamilton, 1987) is far too low. Figure 2(b) shows the fit when the 1979 population estimate is included in the minimisation, in which case hunting mortalities above 15% do not give a good fit even at high selectivity. Another kind of data that can be used to infer the pattern of hunting is the distribution of tusks in the trade. The largest sample of tusks that we have (53 000) is the Singapore stockpile, which represents hunting throughout Africa. Figure 3 shows which combination of hunting mortality and selectivity would produce a tusk weight distribution that best fits that of the Singapore stockpile. It is clear that low selectivity always produces a poor fit. The best fit occurs at an annual hunting mortality of 12% with high selectivity for larger tusks, the best fit being at around a selectivity of 1.6. The least squares fit produces a minimum that matches the peak of the distribution very precisely. However, the long tail of larger tusks visible in the Singapore stockpile is not predicted at this level of selectivity. A method of comparing distributions that concentrates on the overall shape of the distributions (i.e. that takes more account of outlying values) is to minimise
224
E. J. Milner-Gulland, R u t h M a c e
/
/
.2 .<
>.
0.5
~'-
o
0.04
0.06
0.08
0.1
0.12
0.14
0:16
2.2
0.18
HUNTING MORTALITY
(a)
/' i ,/~,/~! ~,
1
o 2
0.6
N
.8
0.5
~
0
0.04
0.06
0.08
0.1
0.12
0.14
0.16
2.2
0.18
HUNTING MORTALITY
Fig. 2. Reciprocal of cumulative residual sum of squares of ivory biomass exported from Africa on predicted biomass for different levels of hunting mortality and selectivity, plotted relative to the least squares fit (i.e. least squares fit -- 1). Population size for 1987 is fixed at 720 000. Population structure, and thus mean tusk weight, is assumed to have stabilised. (a) Least squares fit is at 12.62% hunting mortality, 0.13 selectivity (r 2 = 0"68); (b) Least squares fit when 1979 population estimate is included is 11.74% hunting mortality, 0.04 selectivity (r 2 = 0'78).
Ivory trade and the African elephant
225
1
0.5
~
0 0.04
~
0.06
0.08
0.1
0.12
0.14
0.16
0.18
HUNTING MORTALITY Fig. 3. Reciprocal of cumulative residual sum of squares of tusk weight distribution in the Singapore stockpile on predicted tusk weight distribution in the trade for different levels of hunting mortality and selectivity, plotted relative to least squares fit (i.e. least squares fit = 1). Population structure, and thus mean tusk weight, is assumed to have stabilised. Least squares fit is at 11.94% hunting mortality, selectivity 1.6.
the Hellinger distance between the distributions (Simpson, 1987). This produces a minimum at a hunting mortality of 8"9% and a selectivity of 0"9. The two minima and the tusk weight distribution of the Singapore stockpile are shown in Fig. 4. The Hellinger Distance minimum is clearly a compromise distribution, fitting neither the peak nor the tail of the Singapore stockpile well. In reality hunting pressure is heterogeneous, with a few countries in southern Africa having stable or increasing populations, while other countries have populations in a far worse state than this analysis suggests. The fact that the Hellinger Distance and least squares analysis produce different minima for the tusk weight distribution is likely to be due to this heterogeneity. The peak in the stockpile distribution could be caused by the majority of populations and the long tail by a minority which are not at a heavily hunted, high-selectivity equilibrium.
DISCUSSION Despite the relatively coarse nature of the data, the various sources have produced a fairly consistent story regarding the extent of elephant hunting that has occurred over the last decade. A good fit with all the availabledata is
E. J. Milner-Gulland, Ruth Mace
226
0.45 0.4 0.35
0.3 Z 0.25 o" Pal
0.2 0.15 0.1 0.05
l'0
2'0 3'0 TUSK WEIGHT (KG)
4'0
50
Fig. 4(a). Tusk weight distribution of the Singapore stockpile.
0.45
j
0.,t
0.35 0.3 1 0.25 0,2
0.15 0.1 0.05
0 I
Fig. 4(b).
10
20
30
4'o
50
TUSK WEIGIIT (KG) CUMULATIVE RESIDUAL HELL1NGER DISTANCE
Predicted tusk weight distributions that minimise the least squares fit (solid line) and Hellinger distance (dotted line) against the Singapore stockpile.
found when the hunting mortality is constant at 12-13% of individuals with tusks being killed for the trade per annum. The level of selectivity that produces the best fit varies; the volume of trade does not give us much information about selectivity, but the tusk weight distribution strongly suggests that hunters do select for larger tusks. This very high selectivity is plausible given that larger tusks are more valuable per kilogramme than smaller ones (Milliken, 1989). It is also consistent with the many field studies that show a very female-biassed sex ratio in hunted populations (see Poole & Thomsen, 1989 for a review). We have shown that the observed decline in the volume of ivory leaving
Ivory trade and the African elephant
227
Africa over the period 1979-86 can be explained largely by the decline in the elephant population rather than by one in hunting effort. The recorded biomass of ivory leaving Africa since the imposition of stronger CITES controls in 1986 has, however, declined particularly steeply. This could be because of a genuine decrease in the hunting pressure on the elephant, or because of a decrease in the proportion of the trade reported in customs or CITES statistics. It is very difficult to dissociate the importance of each factor. Population estimates were very inaccurate a decade ago. Our analysis of the trade data suggests that the often-quoted figure of 1 340 000 elephants in 1979 is a minimum, since hunting mortalities below 12% give a poor fit to the data (see Fig. 2). We provide independent verification that the changes in population size and structure observed in the field are consistent with the removal of tusks of the number and size found in the ivory trade. In 1989, most of the countries signatory to the Convention for the International Trade in Endangered Species agreed to stop trading in ivory, which will mean that the type of data analysed in this paper is likely to become difficult or impossible to obtain. As a considerable amount of time and effort has been expended by conservation bodies in collecting such data in the past, it is worth considering whether its loss is likely to have any major implications for the conservation of the elephant. If hunting were to continue at the level at which it has occurred for the previous decade, then we do not predict any great change in mean tusk weight in the trade. An increase in hunting mortality would only produce a small decrease in mean tusk weight when the latter is already low. A total cessation of all hunting would produce a gradual increase in mean tusk weight in the population of 1 kg in 10 years. Thus, changes in tusk weight distribution will be rather insensitive to changes in hunting mortality or selectivity in either direction, and are likely to be well within the considerable margins of error of the data, at least in the medium term. Data on the number of tusks leaving Africa will provide only a limited measure of the success of the trade ban but any estimates of trade would be hard to compare with data from the last decade, which were collected under different circumstances. Because there are increased incentives to misreport ivory at customs, now that most trade is illegal, a decline in ivory shipments reported by customs is likely to be a poor indicator of the effectiveness of a ban. Elephant populations are becoming increasingly fragmented, frequently into areas where monitoring and conservation efforts are concentrated. Thus, over the next decade, field methods of determining hunting mortality (such as carcass counts) are likely to provide a more accurate evaluation of the efficacy of conservation measures such as the trade ban.
228
E.J. Milner-Gulland, Ruth Mace ACKNOWLEDGEMENTS
We would like to thank Marinelle Basson, John Beddington and Mark Bravington for their contributions to this work, the Wildlife Trade Monitoring Unit for access to their database on tusk sizes, which was compiled by John Caldwell, and Cynthia Moss and Iain Douglas-Hamilton for also making unpublished data available to us. Part of this work was carried out for the Ivory Trade Review Group, an independent body reporting to the African Elephant Working Group of the Convention on International Trade in Endangered Species (CITES).
REFERENCES Barnes, R. (1989). The status of elephants in the forests of central Africa: A reconnaissance survey. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Burrill, A. & Douglas-Hamilton, I. (1987). African elephant database project--final report. GRID Case Stud), Series, No. 2. Craig, G. C. (1989). Population dynamics of elephants. In Elephant management in Zimbabwe. Presentation by the Zimbabwe Department of National Parks and Wildlife Management to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989, pp. 67-72. Douglas-Hamilton, I. (1972). Ecology and behaviour of the African elephant. DPhil. thesis, University of Oxford. Douglas-Hamilton, I. (1979). Final Report, African Elephant Trade Study. Report for the US Fisheries and Wildlife Service, Washington, DC. Douglas-Hamilton, I. (1988). African Elephant Population Study Report, United Nations Environment Programme, Nairobi. Fowler, C. W. (1981). Comparative population dynamics in large mammals. In Dynamics of Large Mammal Populations, ed. C. W. Fowler & T. D. Smith. Wiley, Chichester, pp. 437 55. Fowler, C. W. (1984). Density dependence in cetacean populations. Rep. Int. Whal. Commn (Special Issue), No. 6, 373-9. Fowler, C. W. & Smith, T. D. (1973). Characterizing stable populations, and application in the African elephant population. J. Wildlife Manage., 37, 513-23. Getz, W. M. & Haight, R. G. (1989). Population Harvesting. Monographs in Population Biology, No. 27, Princeton University Press, Princeton, NJ. Hanks, J. (1972). Reproduction of elephant, Loxodonta africana, in the Luangwa valley, Zambia. J. Reprod. Fert., 30, 13-26. Jachmann, H. (1986). Notes on the population dynamics of the Kasungu elephants. Afr. J. Ecol., 24, 215 26. Laws, R. M., Parker, I. S. C. & Johnstone, R. C. B. (1975). Elephants and their Habitats. Clarendon Press. Oxford. Leslie, P. H. (1945). On the use of matrices in certain population mathematics. Biometrika, 33, 183-212.
Ivory trade and the African elephant
229
Luxmoore, R., Caldwell, J. 8z Hithersay, L. (1989). The volume of raw ivory entering international trade from African producing countries from 1979 to 1988. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Milliken, T. (1989). The Japanese ivory trade. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Milliken, T. & Melville, D. (1989). The Hong K ong ivory trade. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Parker, I. S. C. (1979). The Ivory Trade. Report for the US Fisheries and Wildlife Service, Washington, DC. Pilgram, T. & Western, D. (1986a). Inferring the sex and age of African elephants from tusk measurements. Biol. Conserv., 36, 39-52. Pilgram, T. & Western, D. (1986b). Inferring hunting patterns on African elephants from tusks in the international ivory trade. J. Appl. Ecol., 23, 503-14. Poole, J. H. (1989). The effects of poaching on the age structure and social and reproductive patterns of selected East African populations. Report to the African Wildlife Foundation, Nairobi. Poole, J. H. & Thomsen, J. B. (1989). Elephants are not beetles. Oryx, 23, 189-98. Sherry, B. Y. (1975). Reproduction of elephant in Gonarezhou, South-East Rhodesia. Arnoldia, 7129), 1-13. Simpson, D. G. (1987). Minimum Hellinger Distance estimation for the analysis of count data. J. Amer. Stat. Assoc., 82(399), 802-7. Smuts, G. L. (1976). Reproductive and population characteristics of elephant in the Kruger National Park. J. Sth Aft. Wildl. Assoc., 5, 1-10. Williamson, B. (1976). Reproduction in female African elephant in the Wankie National Park, Rhodesia. Sth Aft. J. Wildl. Res., 6, 89-93. Wu, L. S.-Y. & Botkin, D. B. (1980). Of elephants and men: A discrete stochastic model for long-lived species with complex life histories. Amer. Nat., 116, 831-49.
The Impact of the Ivory Trade on the African Elephant Loxodonta africana Population as Assessed by Data from the Trade
E. J. Milner-Gulland & Ruth Mace* Renewable Resources Assessment Group, Imperial College Centre for Environmental Technology, 8 Princes Gardens, London SW7 1NA, UK (Received 25 April 1990; accepted 30 June 1990)
A BSTRA CT Data on the total quantity and tusk sizes of African elephant Loxodonta africana ivory entering the international trade over the last decade are reviewed. This work investigated how different levels of hunting and different strengths of selectivity by hunters in favour of larger tusks would produce different ivory tonnages and tusk size distributions in the trade. It shows that the removal of about 12-13% of elephants with tusks each year, combined with hunters showing a preference for elephants with larger tusks, would be expected to produce quantities of ivory and tusk size distributions compatible with those reported in international trade.
INTRODUCTION The ivory trade in Africa has a long history, recounted in detail by Parker (1979). At the turn of the century, volumes of trade were high. With the collapse of the slave trade (with which the ivory trade was intimately associated) and the coming of the two world wars, hunting was much reduced. Volumes of trade grew slowly through the 1950s and 1960s but it was only in the 1970s, as Asian and Far Eastern countries--especially Japan--became wealthy, that a massive increase in elephant (Loxodonta * Present address: School of Development Studies, University of East Anglia, Norwich NR4 7JT, UK. 215 Biol. Conserv. 0006-3207/90/$03'50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Great Britain
216
E. J. Milner-Gulland, Ruth Mace
africana) hunting occurred. The elephant population had to supply a new demand as large as, or larger than, that of the colonial period. In order to explore the way in which harvesting could affect elephant populations, we constructed a Leslie matrix model (Leslie, 1945), which tracks the population through time, by age-class and sex. This approach is particularly appropriate for the exploration of the effects of trade on elephant populations since the relationship between tusk size and age is described by a power law for both sexes, but male tusks grow at a much faster rate than female tusks (Pilgram & Western, 1986a). Since male tusks are visible at a younger age they also start to be hunted at a younger age than females. If any form of selectivity in favour of larger tusks occurs, then males and older animals will suffer more hunting than females and immatures. It is therefore important that the age and sex structure of the population be taken into account. There have been several models of elephant population biology that use the Leslie matrix, for example to model the relationship between elephant populations and their habitats (Fowler & Smith, 1973; Wu & Botkin, 1980) and to model elephant harvesting strategies (Pilgram & Western, 1986b; Getz & Haight, 1989). In this study we used a Leslie matrix model to help interpret actual data from the international ivory trade.
D A T A SOURCES Two complementary types of trade data were used to assess the impact of trade on the African elephant population: the total biomass in international trade and the size distribution of tusks in the trade. Estimates of the total biomass of ivory in international trade give only a limited idea of the number of elephants killed to supply the trade without data on the mean tusk weight in the trade. Tusk weight distributions provide mean tusk weights, together with some information on the age and sex composition of the offtake and thus, the population. Each source of data has the potential for considerable inaccuracy, but by using both we can see to what extent a consistent story emerges about the nature and consequences of the hunting that has occurred to supply the international ivory trade. Estimates of elephant population size give some indication of population change over the decade, which can be compared to that given by the trade data.
Population surveys Data on population size are available from various sources for the period 1979-89, but they are subject to large margins of error due to changes in
Ivory trade and the African elephant
217
sampling methods and estimation techniques and to a large component of extrapolation (Burrill & Douglas-Hamilton, 1987). There is particular uncertainty as to the number of elephants in the central African forests. Estimates for 1987 and 1989 have been revised on the basis of recent survey work in these forests (Barnes, 1989), and are thought to be much more accurate than previous estimates, partly due to the use of the UNEP G R I D system to extrapolate from the best available data for each region of Africa.
Exports of ivory from Africa Data on the volume of trade in ivory over the period 1979-87 are available for each ivory exporting country in Africa (Luxmoore et al., 1989). These are predominately customs records from importing countries, indicating from which country the ivory came, which tend to be more reliable than records from exporting countries. The mean annual export of raw ivory from Africa has been over 700 tonnes for the last decade. The figure was somewhat higher than this in the early 1980s and has been declining gradually throughout the decade. It dropped particularly steeply in 1987, although Luxmoore et al. (1989) advise treating this last figure with caution. All estimates of the volume of the ivory trade must be treated as minima since not only do they exclude ivory carved within the country of origin, but also an unknown proportion of illicit trade. Although it is clear that the hunting pressure on the African elephant is heterogeneous, the characteristics of the ivory trade are such that it would be unwise to attempt to relate a country's exports directly to changes in that country's elephant population, and so to build up a less superficial view of the effects of the trade on elephant populations. The illicit nature of much of the ivory trade means that the exports of a particular country may have more to do with the efficiency of its Customs and border patrols, and the strength of its currency, than the status of its elephant population. Africa-wide exports at least tell us the total volume of ivory removed from the total population.
The size of tusks in the trade The weights of individual tusks legally exported from various countries in Africa between 1986 and 1988 are available from an analysis of CITES export permits in those years by the Wildlife Trade Monitoring Unit of the International Union for the Conservation of Nature. For the majority of countries the median tusk weight is below 5 kg, but the exports of three countries (Congo, Gabon, Zimbabwe) have median tusk weights around 10kg, indicating that these countries were exporting only a selection of larger tusks. A smaller sample of tusks from the government ivory stores of
218
E. J. Milner-Gulland, Ruth Mace
various African countries in the period 1979-1981 was also analysed. The mean tusk weight for the 1979-81 sample, with the mean tusk weight from each country weighted according to its total exports, is 4-97 kg, and for the 1986-88 sample 4.52 kg (excluding the above-named selective exporters). Tusk weight distributions are also available for the Singapore stockpile registered by CITES in 1986, and for ivory confiscated in Tanzania over the period 1971-77 and in Kenya in 1986-88 (I. Douglas-Hamilton, pers. comm.). The sample sizes and mean and median tusk weights for the samples are shown in Table 1. Tusk weight distributions tend to be very skewed towards smaller tusks, as is shown by the difference between the mean and median. There is no evidence from the above tusk weight distributions that the mean tusk weight o f ivory entering the trade has declined greatly since 1979. For the three countries where there are data in more than one time period, one country showed a small increase in mean tusk weight, one a small decrease and one an increase followed by a decrease. Data collected from major importing countries do seem to show a decline in mean tusk weight over this period, this being rather sharp in some cases (Milliken, 1989; Milliken & Melville, 1989). These data must be interpreted with great care, since importing countries are selective in their buying, and this is reflected
TABLE 1
Total Numbers of Tusks for which Mean and Median Tusk Weights were Available, including only those Countries with a Total Sample Size of at least 1000 Tusks Country
1979-81 Sample size
Burundi Congo Djibouti Gabon Kenya Mozambique Sudan Tanzania (1971-77) Singapore South Africa Zambia Zaire Zimbabwe
Mean
1986-88 Median
835
4.20
2-61
2 639 44 055
5-09 4.98
3'60 3.41
1 302
4.85
3.61
Sample size
Mean
Median
17841 5 392 1981 1 532 1957 3 049 33 580 8 488
4.95 12.43 5"49 11.74 5'60 5.71 3.54 4"57
3.32 11.32 3.39 10'53 4.27 3.62 2.11 2'86
52 823 10 640 2 723 4 283 1481
4-87 7"11 4"37 4,39 11,37
3"33 4.48 2.87 2.57 9-11
All data supplied by WTMU except the confiscated tusks from Kenya and Tanzania, supplied by I. Douglas-Hamilton (pers. comm.).
Ivory trade and the African elephant
219
in the large difference in mean tusk weights imported by different countries. The mean weight of all tusks circulating in world trade (Milliken, 1989), was much lower in 1986-87 than in the previous few years.
A S I M U L A T I O N M O D E L OF E L E P H A N T P O P U L A T I O N DYNAMICS: A S S U M P T I O N S A N D P A R A M E T E R VALUES In a Leslie matrix model, the number of animals in each age-class in a year is calculated as the number of animals in the previous age class in the previous year, minus those that died as a result of natural mortality or hunting. The number of animals in the first age-class is calculated from the number of calves that the female population would have given birth to in the previous year. We assume that animals with tusks of less than 1 kg (i.e. females less than nine years old and males younger than six) are not hunted, as tusks smaller than this are rare in the trade. But although calves are not killed directly many die when their mothers are killed. Poole (1989) gives data on the mortality rates of orphaned calves, which are incorporated in the model. Mortality is taken to occur sequentially, with half the natural mortality occurring first, followed by hunting mortality and incidental calf mortality caused by orphaning, then the other half of the natural mortality. Finally, recruitment occurs. The tusk weight distributions of offtake produced by the model includes only hunted elephants. Natural mortality tusks (including those from orphaned calves) are assumed not to be found. Studies have shown that even in the best-patrolled national parks, the finding rate for natural mortality tusks is less than 6% of those available (Douglas-Hamilton, 1979), and so it is unlikely that natural mortality makes up a large proportion of trade. This is particularly so at high levels of hunting mortality, when few adult animals will survive long enough to die a 'natural death', and the smaller tusks resulting from the deaths of immatures are much more likely to disintegrate or be eaten by hyaenas, as well as being harder to locate. The parameter values used in the model are shown in Table 2. In reality there will be considerable variation between populations due to a variety of factors such as rainfall, which will vary locally and from year to year; the values given are therefore averages. Density-dependent effects on reproduction are not included in the model, unlike in other models of the effects of harvesting on elephant populations (Pilgram & Western, 1986a). This is because of the fact that, as a large mammal with a low intrinsic rate of reproduction, the elephant is only likely to show significantly reduced reproduction due to high population density when at over 75-80% of carrying capacity (Fowler, 1981, 1984). Studies of
E.J. Milner-Gulland, Ruth Mace
220
t~
~=~
"8 o
~o
.~
.~ 0 e~
o
"~
0
0 .0
0
.,-
<.=. 0 .~,
.=
0
r~
0
I
O
e-,
u~ ell
_= > r~
E
2 .~
E
.m
~ ~ ~ ~ -~ ~ - ~ ~
~ ~ ~
.~ ~
._="
E
~
.o ~ ~
~
~
'~.~
~ ~
e-,
o
r.~
z
Ivory trade and the African elephant
221
the density of elephant populations (Douglas-Hamilton, 1988) suggest that it is only in a very few parks that densities may approach these high levels and we assume that this was already the case by 1979. More worrying is the suggestion by Poole (1989) that reproductive rates drop at high hunting levels due to a shortage of males and/or social disruption, in some cases dramatically. We assume an interbirth interval of five years. Whereas populations that are at low densities but are freed from hunting may be breeding faster than we have estimated, populations that are being lowered by continuous poaching may be breeding very much more slowly. Decreasing the assumed interbirth interval reduced the goodness of fit in the analyses presented in our results, while increasing it made little difference. Thus, a five-year interbirth interval seems a realistic assumption. Selectivity was modelled assuming that hunter preference was related to the weight of the tusk (see Table 2). A selectivity of 0 means that each age class is hunted in proportion to the frequency with which it appears in the population. Thus, at a 12% hunting mortality, 12% of each age class is taken per year. A selectivity of 1 means that tusks are preferred directly in proportion to their weight, for example an elephant with 6 kg tusks is twice as likely to be hunted as one with 3 kg tusks. A selectivity of 2 means that the 6 kg tusker is four times as likely to be hunted as the 3 kg tusker. The hunting mortalities in this paper are expressed as the proportion of the total number of animals available for hunting that is killed each year. This proportion is divided among the age-classes according to the strength of the selectivity. If the hunting mortality were taken as a proportion of the whole population, it would be lower. However, the deaths of orphaned calves as an indirect result of hunting mean that the hunting-induced mortality in these age-classes is approximately the same as that for adult females. Exact figures depend on the age and sex structure of the population. The model shows that a population with these dynamics would remain stable and stationary if no more than 3.5 % of the available age-classes were hunted per year (note that this is higher than the hunting rate that would yield the maximum sustainable yield in terms of ivory biomass (M. Basson, pers. comm.). This figure is similar to that estimated, by a different method, to be an appropriate culling rate to keep elephant populations in Zimbabwe at a stable size (Craig, 1989). RESULTS
The effect of hunting patterns on the size of tusks entering the trade The strategy used to hunt elephants will have a direct effect on the weight distribution of tusks in the trade, and thus on the biomass produced when a
222
E. J. Milner-Gulland, Ruth Mace
particular number of animals is killed. This study explored the effects on population size and ivory supply of varying both the proportion of the population taken each year and the strength of the selectivity shown by hunters for larger tusks. When a pristine population is first subjected to hunting the size of tusks harvested will decline. If the hunters are not selective, then tusks in the trade will reflect those in the population (except calves with tusks of less than 1 kg). Mean tusk size harvested will decline as the mean age of the population declines. The greater the selectivity for larger tusks, the faster the rate of initial decline in mean tusk weight as adult males, and then younger males and adult females are removed from the population at a disproportionate rate. Whilst this decline is initially rapid, the tusk size distribution produced soon reaches a state of relative stability or negligible decline, where it remains until extinction occurs. For any given hunting mortality, the higher the selectivity, the lower the mean tusk weight at which the population (and offtake) stabilises. The weight distribution of tusks in the trade stabilises even while the population size is declining rapidly. If hunting were at 12% per year with selectivity 1, then the mean tusk weight would fall by 10kg in the first 10 years, then by less than 1 kg in the next 40 years, while the population halved every 10 years. When fitting total ivory tonnages we assume that populations are no longer in the phase of rapid decline but in the relatively stable phase, given the tusk weight data shown above. Although it is unlikely that most populations are stable, the data suggest that most are not in the phase of rapid decline. Thus, for a given set of life history parameters, the combination of the hunting mortality and selectivity applied to a population will determine the rate of decline of that population, the tonnes of ivory produced and the size distribution of the tusks. Finding the best fit to available data
The combination of hunting mortality and selectivity that minimises the sum of squares of the residuals between the result predicted by the model and observed data (i.e. the least squares fit) is calculated for (i) biomass in the trade since 1979; (ii) biomass in the trade since 1979 and the 1979 population estimate; (iii) the tusk weight distribution of the Singapore stockpile. The population size in 1987 is fixed at 720 000 animals (Douglas-Hamilton, 1988) because the 1987 population estimate is considered to be the most accurate datapoint available. The biomass reported in international trade since 1979 best fits an annual
Ivory trade and the African elephant
223
1100 -I
900 Z Z
800
O [..
es~
700
.< (D
-1,-__
600 50O 400 300 1979
1 80
' 1981
19~82
' 1983 YEAR
' 1984
~ 1985
' 1986
1987
Fig. I. T o t a l b i o m a s s in t o n n e s o f ivory e x p o r t e d f r o m Africa in the years 1979-87, with e x p e c t e d b i o m a s s u n d e r the h u n t i n g p a t t e r n that m i n i m i s e s the least s q u a r e s fit b e t w e e n m o d e l o u t p u t a n d b i o m a s s data. D a t a f r o m L u x m o o r e et al. (1989). P o p u l a t i o n size for 1987 is fixed at 720000.
hunting mortality of 12"6% at a selectivity of 0.1 (Fig. 1). Figure 2(a) shows how sensitive this fit is to variation in hunting mortality and selectivity. Hunting mortalities of less than 12% do not produce a good fit at any level of selectivity. Hunting mortalities as high as 17% do give a reasonable fit as long as the selectivity is high. If such high levels of hunting mortality have occurred, then the 1979 population estimate of 1 340000 elephants (Burrill & Douglas-Hamilton, 1987) is far too low. Figure 2(b) shows the fit when the 1979 population estimate is included in the minimisation, in which case hunting mortalities above 15% do not give a good fit even at high selectivity. Another kind of data that can be used to infer the pattern of hunting is the distribution of tusks in the trade. The largest sample of tusks that we have (53 000) is the Singapore stockpile, which represents hunting throughout Africa. Figure 3 shows which combination of hunting mortality and selectivity would produce a tusk weight distribution that best fits that of the Singapore stockpile. It is clear that low selectivity always produces a poor fit. The best fit occurs at an annual hunting mortality of 12% with high selectivity for larger tusks, the best fit being at around a selectivity of 1.6. The least squares fit produces a minimum that matches the peak of the distribution very precisely. However, the long tail of larger tusks visible in the Singapore stockpile is not predicted at this level of selectivity. A method of comparing distributions that concentrates on the overall shape of the distributions (i.e. that takes more account of outlying values) is to minimise
224
E. J. Milner-Gulland, R u t h M a c e
/
/
.2 .<
>.
0.5
~'-
o
0.04
0.06
0.08
0.1
0.12
0.14
0:16
2.2
0.18
HUNTING MORTALITY
(a)
/' i ,/~,/~! ~,
1
o 2
0.6
N
.8
0.5
~
0
0.04
0.06
0.08
0.1
0.12
0.14
0.16
2.2
0.18
HUNTING MORTALITY
Fig. 2. Reciprocal of cumulative residual sum of squares of ivory biomass exported from Africa on predicted biomass for different levels of hunting mortality and selectivity, plotted relative to the least squares fit (i.e. least squares fit -- 1). Population size for 1987 is fixed at 720 000. Population structure, and thus mean tusk weight, is assumed to have stabilised. (a) Least squares fit is at 12.62% hunting mortality, 0.13 selectivity (r 2 = 0"68); (b) Least squares fit when 1979 population estimate is included is 11.74% hunting mortality, 0.04 selectivity (r 2 = 0'78).
Ivory trade and the African elephant
225
1
0.5
~
0 0.04
~
0.06
0.08
0.1
0.12
0.14
0.16
0.18
HUNTING MORTALITY Fig. 3. Reciprocal of cumulative residual sum of squares of tusk weight distribution in the Singapore stockpile on predicted tusk weight distribution in the trade for different levels of hunting mortality and selectivity, plotted relative to least squares fit (i.e. least squares fit = 1). Population structure, and thus mean tusk weight, is assumed to have stabilised. Least squares fit is at 11.94% hunting mortality, selectivity 1.6.
the Hellinger distance between the distributions (Simpson, 1987). This produces a minimum at a hunting mortality of 8"9% and a selectivity of 0"9. The two minima and the tusk weight distribution of the Singapore stockpile are shown in Fig. 4. The Hellinger Distance minimum is clearly a compromise distribution, fitting neither the peak nor the tail of the Singapore stockpile well. In reality hunting pressure is heterogeneous, with a few countries in southern Africa having stable or increasing populations, while other countries have populations in a far worse state than this analysis suggests. The fact that the Hellinger Distance and least squares analysis produce different minima for the tusk weight distribution is likely to be due to this heterogeneity. The peak in the stockpile distribution could be caused by the majority of populations and the long tail by a minority which are not at a heavily hunted, high-selectivity equilibrium.
DISCUSSION Despite the relatively coarse nature of the data, the various sources have produced a fairly consistent story regarding the extent of elephant hunting that has occurred over the last decade. A good fit with all the availabledata is
E. J. Milner-Gulland, Ruth Mace
226
0.45 0.4 0.35
0.3 Z 0.25 o" Pal
0.2 0.15 0.1 0.05
l'0
2'0 3'0 TUSK WEIGHT (KG)
4'0
50
Fig. 4(a). Tusk weight distribution of the Singapore stockpile.
0.45
j
0.,t
0.35 0.3 1 0.25 0,2
0.15 0.1 0.05
0 I
Fig. 4(b).
10
20
30
4'o
50
TUSK WEIGIIT (KG) CUMULATIVE RESIDUAL HELL1NGER DISTANCE
Predicted tusk weight distributions that minimise the least squares fit (solid line) and Hellinger distance (dotted line) against the Singapore stockpile.
found when the hunting mortality is constant at 12-13% of individuals with tusks being killed for the trade per annum. The level of selectivity that produces the best fit varies; the volume of trade does not give us much information about selectivity, but the tusk weight distribution strongly suggests that hunters do select for larger tusks. This very high selectivity is plausible given that larger tusks are more valuable per kilogramme than smaller ones (Milliken, 1989). It is also consistent with the many field studies that show a very female-biassed sex ratio in hunted populations (see Poole & Thomsen, 1989 for a review). We have shown that the observed decline in the volume of ivory leaving
Ivory trade and the African elephant
227
Africa over the period 1979-86 can be explained largely by the decline in the elephant population rather than by one in hunting effort. The recorded biomass of ivory leaving Africa since the imposition of stronger CITES controls in 1986 has, however, declined particularly steeply. This could be because of a genuine decrease in the hunting pressure on the elephant, or because of a decrease in the proportion of the trade reported in customs or CITES statistics. It is very difficult to dissociate the importance of each factor. Population estimates were very inaccurate a decade ago. Our analysis of the trade data suggests that the often-quoted figure of 1 340 000 elephants in 1979 is a minimum, since hunting mortalities below 12% give a poor fit to the data (see Fig. 2). We provide independent verification that the changes in population size and structure observed in the field are consistent with the removal of tusks of the number and size found in the ivory trade. In 1989, most of the countries signatory to the Convention for the International Trade in Endangered Species agreed to stop trading in ivory, which will mean that the type of data analysed in this paper is likely to become difficult or impossible to obtain. As a considerable amount of time and effort has been expended by conservation bodies in collecting such data in the past, it is worth considering whether its loss is likely to have any major implications for the conservation of the elephant. If hunting were to continue at the level at which it has occurred for the previous decade, then we do not predict any great change in mean tusk weight in the trade. An increase in hunting mortality would only produce a small decrease in mean tusk weight when the latter is already low. A total cessation of all hunting would produce a gradual increase in mean tusk weight in the population of 1 kg in 10 years. Thus, changes in tusk weight distribution will be rather insensitive to changes in hunting mortality or selectivity in either direction, and are likely to be well within the considerable margins of error of the data, at least in the medium term. Data on the number of tusks leaving Africa will provide only a limited measure of the success of the trade ban but any estimates of trade would be hard to compare with data from the last decade, which were collected under different circumstances. Because there are increased incentives to misreport ivory at customs, now that most trade is illegal, a decline in ivory shipments reported by customs is likely to be a poor indicator of the effectiveness of a ban. Elephant populations are becoming increasingly fragmented, frequently into areas where monitoring and conservation efforts are concentrated. Thus, over the next decade, field methods of determining hunting mortality (such as carcass counts) are likely to provide a more accurate evaluation of the efficacy of conservation measures such as the trade ban.
228
E.J. Milner-Gulland, Ruth Mace ACKNOWLEDGEMENTS
We would like to thank Marinelle Basson, John Beddington and Mark Bravington for their contributions to this work, the Wildlife Trade Monitoring Unit for access to their database on tusk sizes, which was compiled by John Caldwell, and Cynthia Moss and Iain Douglas-Hamilton for also making unpublished data available to us. Part of this work was carried out for the Ivory Trade Review Group, an independent body reporting to the African Elephant Working Group of the Convention on International Trade in Endangered Species (CITES).
REFERENCES Barnes, R. (1989). The status of elephants in the forests of central Africa: A reconnaissance survey. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Burrill, A. & Douglas-Hamilton, I. (1987). African elephant database project--final report. GRID Case Stud), Series, No. 2. Craig, G. C. (1989). Population dynamics of elephants. In Elephant management in Zimbabwe. Presentation by the Zimbabwe Department of National Parks and Wildlife Management to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989, pp. 67-72. Douglas-Hamilton, I. (1972). Ecology and behaviour of the African elephant. DPhil. thesis, University of Oxford. Douglas-Hamilton, I. (1979). Final Report, African Elephant Trade Study. Report for the US Fisheries and Wildlife Service, Washington, DC. Douglas-Hamilton, I. (1988). African Elephant Population Study Report, United Nations Environment Programme, Nairobi. Fowler, C. W. (1981). Comparative population dynamics in large mammals. In Dynamics of Large Mammal Populations, ed. C. W. Fowler & T. D. Smith. Wiley, Chichester, pp. 437 55. Fowler, C. W. (1984). Density dependence in cetacean populations. Rep. Int. Whal. Commn (Special Issue), No. 6, 373-9. Fowler, C. W. & Smith, T. D. (1973). Characterizing stable populations, and application in the African elephant population. J. Wildlife Manage., 37, 513-23. Getz, W. M. & Haight, R. G. (1989). Population Harvesting. Monographs in Population Biology, No. 27, Princeton University Press, Princeton, NJ. Hanks, J. (1972). Reproduction of elephant, Loxodonta africana, in the Luangwa valley, Zambia. J. Reprod. Fert., 30, 13-26. Jachmann, H. (1986). Notes on the population dynamics of the Kasungu elephants. Afr. J. Ecol., 24, 215 26. Laws, R. M., Parker, I. S. C. & Johnstone, R. C. B. (1975). Elephants and their Habitats. Clarendon Press. Oxford. Leslie, P. H. (1945). On the use of matrices in certain population mathematics. Biometrika, 33, 183-212.
Ivory trade and the African elephant
229
Luxmoore, R., Caldwell, J. 8z Hithersay, L. (1989). The volume of raw ivory entering international trade from African producing countries from 1979 to 1988. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Milliken, T. (1989). The Japanese ivory trade. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Milliken, T. & Melville, D. (1989). The Hong K ong ivory trade. In The Ivory Trade and the Future of the African Elephant. Report of the Ivory Trade Review Group to the Seventh CITES Conference of the Parties, Lausanne, 9-20 October 1989. Parker, I. S. C. (1979). The Ivory Trade. Report for the US Fisheries and Wildlife Service, Washington, DC. Pilgram, T. & Western, D. (1986a). Inferring the sex and age of African elephants from tusk measurements. Biol. Conserv., 36, 39-52. Pilgram, T. & Western, D. (1986b). Inferring hunting patterns on African elephants from tusks in the international ivory trade. J. Appl. Ecol., 23, 503-14. Poole, J. H. (1989). The effects of poaching on the age structure and social and reproductive patterns of selected East African populations. Report to the African Wildlife Foundation, Nairobi. Poole, J. H. & Thomsen, J. B. (1989). Elephants are not beetles. Oryx, 23, 189-98. Sherry, B. Y. (1975). Reproduction of elephant in Gonarezhou, South-East Rhodesia. Arnoldia, 7129), 1-13. Simpson, D. G. (1987). Minimum Hellinger Distance estimation for the analysis of count data. J. Amer. Stat. Assoc., 82(399), 802-7. Smuts, G. L. (1976). Reproductive and population characteristics of elephant in the Kruger National Park. J. Sth Aft. Wildl. Assoc., 5, 1-10. Williamson, B. (1976). Reproduction in female African elephant in the Wankie National Park, Rhodesia. Sth Aft. J. Wildl. Res., 6, 89-93. Wu, L. S.-Y. & Botkin, D. B. (1980). Of elephants and men: A discrete stochastic model for long-lived species with complex life histories. Amer. Nat., 116, 831-49.